Untitled

R Markdown

This is an R Markdown document. Markdown is a simple formatting syntax for authoring HTML, PDF, and MS Word documents. For more details on using R Markdown see http://rmarkdown.rstudio.com.

When you click the Knit button a document will be generated that includes both content as well as the output of any embedded R code chunks within the document. You can embed an R code chunk like this:

library(tidyverse)
library(plotly)
if(!require(readr)) {
  install.packages('readr')
  library(readr)
}

if(!require(lubridate)) {
  install.packages('lubridate')
  library(lubridate)
}

covid19_df <- read_csv(file = "D:/R/data/owid-covid-data.csv",
                            col_types = cols(Date = col_date(format = "%Y-%m-%d")
                                             )
                            )

covid19_df <- read_csv(file = "https://covid.ourworldindata.org/data/owid-covid-data.csv",
                            col_types = cols(Date = col_date(format = "%Y-%m-%d")
                                             )
                            )


covid19_df_100 <- covid19_df |> 
  filter((iso_code %in% c('KOR', 'OWID_ASI', 'OWID_EUR', 'OWID_OCE', 'OWID_NAM', 'OWID_SAM'))) |>
  filter(date >= today() - 100) |> 
  arrange(date)

covid19_df_100_wide <- covid19_df_100 |> select(date, location, new_cases) |> 
  pivot_wider(id_cols = date, names_from = location, values_from = new_cases) |> 
  arrange(date)

## 공백을 쓰려면 ``
names(covid19_df_100_wide) <- c('date', 'Asia', 'Europe', 'North_America', 'Oceania', 'South_America', 'South_Korea')

covid19_stat <- covid19_df |> group_by(iso_code, continent, location) |>
  summarise(인구수 = max(population, na.rm = T), 인당GDP = max(gdp_per_capita, na.rm = T),
            전체확진자수 = sum(new_cases, na.rm = T),
            전체사망자수 = sum(new_deaths, na.rm = T), 
            십만명당사망자수 = round(total_deaths / population *100000, 5),
            십만명당중환자실 = last(icu_patients_per_million),
            재생산지수 = last(reproduction_rate),
            전체검사자수 = max(total_tests, na.rm = T), new_tests = sum(new_tests, na.rm = T),
            전체백신접종자수 = max(total_vaccinations, na.rm = T),
            백신접종자완료자수 = max(people_fully_vaccinated, na.rm = T),
            부스터접종자수 = max(total_boosters, na.rm = T),
            백신접종완료률 = people_fully_vaccinated / population,
            인구백명당백신접종완료률 = max(people_fully_vaccinated_per_hundred, na.rm = T),
            인구백명당부스터접종자수 = max(total_boosters_per_hundred, na.rm = T)
            ) |> ungroup()

margins <- list(t = 50, b = 25, l = 25, r = 25)

Including Plots

You can also embed plots, for example:

covid19_df_100 |> filter(iso_code == 'KOR') |> 
  plot_ly(x = ~date, y = ~new_cases) |>
  layout(title = '최근 100일간 우리나라 코로나 19 확진자 수', 
         xaxis = list(title = ''),
         yaxis = list(title = '확진자수'), 
         margin = margins)

fig <- covid19_df_100 |> filter(iso_code == 'KOR') |> 
  plot_ly(x = ~date, y = ~new_cases) |>
  layout(title = '최근 100일간 우리나라 코로나 19 확진자 수', 
         xaxis = list(title = ''),
         yaxis = list(title = '확진자수'), 
         margin = margins)

fig <- fig |> as.widget()

fig

Note that the echo = FALSE parameter was added to the code chunk to prevent printing of the R code that generated the plot.